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The worldwide growing demand for energy has imposed much pressure on energy supply and the environment. Solar energy, as one of the clean and renewable resources, provides a great potential for helping to meet the growing energy demand and reduce the environmental impacts. How to make the best use of a solar photovoltaic (PV) system has received much attention in recent years. Integrating geographic information systems (GIS), this paper proposes a new spatial optimization problem, the maximal PV panel coverage problem (MPPCP), for solar PV panel layout design. Suitable installation areas are first delineated in GIS. Then the MPPCP is used to identify the best spatial configurations of multiple PV panels. Different orientations and alignment scenarios are incorporated in the model to account for installation constraints while achieving the goal of maximal energy production. The new problem is applied to locate solar PV arrays on a rooftop with limited suitable installation areas. Results show that flexible panel alignments increase the maximal energy production by up to 6%. Model performance and computational efficiency are discussed. The research provides important insights into the spatial layout design of solar PV panels at various scales. • GIS finds the suitable areas for solar PV panel installation. • Layout design maximizes the energy production potential of a solar PV system. • The new method has been applied to identify the optimal panel layout on a rooftop. • Flexible panel alignments increase the maximal energy production by up to 6%. • Model 1 is more computational tractable requiring less problem-solving time. [ABSTRACT FROM AUTHOR]

• Optimizing community gardens could ensure equal access to food and cooling benefits during urban sprawl. • Compared to ad-hoc planning, optimization systematically identifies the optimal number and locations of gardens. • In warm/hot arid climates, more gardens are needed to mitigate urban heat than food-desert. • Food-desert or heat mitigation alone cannot optimize either's challenge. • Tradeoffs between the two are critical, especially when a small number of gardens are sited. Urban community gardens can reduce food insecurity and serve as green spaces alleviating extreme temperatures. Such co-benefit synergy may prove especially significant for arid-land metropolises. Despite these synergistic roles, planning for community gardens is largely undertaken in an ad-hoc manner. To date, few studies have addressed the full potential (co-benefits) of developing urban vacant land into community garden-green spaces. We addressed this in a spatially-optimized way, developing a model seeking to mitigate food desert and urban heat, and applied it to the fast sprawling Phoenix metro-area, Arizona (USA). Examining more than 5,000 vacant parcels for potential garden-green spaces, we found that the optimal number and locations of community gardens needed for different mitigation goals can vary significantly. In the Phoenix metro-area, the gardens required for extreme heat mitigation is about twice the number for food desert mitigation because high-temperature areas are more prevalent and expansive in semi-arid desert environment compared to the relatively small number low income, food desert areas. Furthermore, we found that the existing 76 community gardens were mostly clustered around urban cores, leaving two-thirds of the metro-area underserved. If sited in a spatially-optimized way, the co-benefits gained from the 76 gardens could be doubled, and covering more high-need neighborhoods. Integrating fine-scale vacant parcel data, our model identified high potential community garden-greening sites in priority neighborhoods with a precision not capable in conventional planning methods. Our findings demonstrate that spatially-optimized planning is of particular importance to avoid clustering of community gardens and ensure more equal access to local food and outdoor cooling benefits. [ABSTRACT FROM AUTHOR]

Covering models have been used in a wide range of modeling and geospatial analysis applications ranging from planning emergency services to natural reserve design. One topic in coverage modeling that has received considerable research attention is addressing uncertainty due to facility unavailability and service disruptions. In this article, we propose a covering model that maximizes the expected coverage of demand by considering the possibility of facility failures. Unlike existing models that assume a uniform failure probability across all sites in an area, the proposed model can account for spatially varying failure probabilities and describes better the underlying geographic processes that cause facility failures. The model is posed as a spatial optimization problem using integer linear programming. We compare two different formulations of the covering model and discuss their properties. The proposed model formulations have been tested computationally using a warning sirens data set that has been widely used in assessing covering models. We conclude with a summary of findings as well as possible directions of future research. [ABSTRACT FROM PUBLISHER]

This article discusses spatial optimization in geography, focusing on contributions of geographers in explicit geographical contexts. An overview of spatial optimization is given, as well as illustrative examples. Many of the individuals contributing to this area of the discipline are identified, demonstrating the breadth of academic institutions spanning the globe where spatial optimization is represented in the research and curriculum of geographers. The article provides a characterization of what a spatial optimization problem is, but also properties, relationships, and challenges behind this. The ultimate purpose of this article is to highlight the spatial optimization subspecialty within geography and in doing so, highlight the need for continued spatial model development and application in the discipline. Further, there is also a need for research focused on techniques to solve spatial optimization problems, particularly in the context of geographic information systems. [ABSTRACT FROM PUBLISHER]

As an emerging technology, wireless communication revolutionizes the way data are shared and transferred. In particular, wireless mesh network (WMN) technology allows data transmission from one node to another without extensive cabling. In this article, spatial characteristics of maximal covering problems are explored, and a novel spatial optimization model is proposed for WMN topology planning. The model selects the optimal locations for network infrastructure to achieve the maximal coverage of spatial demand. Additionally, important WMN design requirements have been accounted for, including network topology and throughput capacity. The validity of the model is tested through a WMN deployment developed for an emergency medical service application in Tucson, Arizona. [ABSTRACT FROM AUTHOR]

Access to a variety of affordable and healthy food has been a critical component in sustainable food-system planning. Research on food accessibility and food deserts (low-income areas with no or limited access to healthy food) can have important policy implications for alleviating health disparities. In the existing food access literature, supermarkets or large chain grocery stores have typically been used as the basis for measuring food access. Independent/non-chain grocers are often left out. We propose a multidimensional accessibility based assessment method to examine whether and how independent grocers help shape the food landscape and their locational strategy. A food desert elimination optimization model is formulated to evaluate the effectiveness of relying on small, full-service grocers for servicing food desert neighborhoods. The empirical study conducted in Tucson, Arizona indicates that, while full-service independent grocers fill some gaps left by chain markets, such stores are more helpful for improving food access diversity; this is reflected by the co-locating patterns of chain and non-chain stores. A few independent stores do, however, primarily serve food deserts in racially/ethnically diverse neighborhoods where higher proportions of residents rely on public assistance program and have limited mobility. Our case study suggests that small, independent grocers may have significant potential to aid in servicing areas with no or limited access to healthy food, particularly if policy incentives are provided. • We examined the role of full service independent grocery stores in shaping urban foodscape. • A spatial optimization model was developed to maximally eliminate food deserts. • Independent grocers are found to fill in the gaps left behind by chain stores in some communities while in many more add to the diversity rather than proximity. • They tend to serve more racially/ethnically diversified and dense neighborhoods. • Promoting small independent grocers in un- or underserved areas has great potential to improve regional food accessibility. [ABSTRACT FROM AUTHOR]

• Converting urban vacant land into food production sites helps increase healthy food access. • Harvested rainwater and reclaimed water can substantially enhance urban food production capability. • A new spatial optimization model is developed to optimize urban food production. • High level of community collaboration helps achieve more food production. • Urban food production has a great potential for addressing urban food deserts. Adequate access to healthy, affordable food remains a great challenge in many urban areas. Among a range of interventions, urban agriculture has been identified as an important strategy to help address urban healthy food access. While urban food production is growing in popularity, the use of potable water in traditional urban agricultural installations will exacerbate gaps in water demand and availability in water-stressed cities. This paper examines the sustainable capability of urban agriculture through an integration of alternative water resources, urban vacant land and local nutritional needs. A spatial optimization model is developed to best allocate limited resources for maximal food production to address urban food deserts. The new model is applied to test the capability of relocalized food production in Tucson, Arizona, a semi-arid region with the longest continuously farmed landscape in North America. Results highlight that urban areas with restricted water access can substantially enhance their local food production capacity in an ecologically responsible manner. [ABSTRACT FROM AUTHOR]

• A novel maximum cover location problem is developed for rooftop PV panel layout. • High resolution images of three distinct rooftop structures are collected with a UAV. • Rooftop structure, panel size, and irradiance determine optimal PV panel layout. • Results highlight the importance of considering panel layout for energy estimates. • The framework provides a spatially explicit optimized panel configuration for each rooftop. Recent years have seen a substantial increase in energy produced by renewable sources. The International Energy Agency (IEA) expects a large portion of future growth in renewable energy to come from solar, especially rooftop photovoltaic (PV) systems. Studies focused on estimating rooftop solar energy potential generally use the total area available for PV installation as determined by solar irradiance availability. This process can lead to substantial over- or under-estimation of energy estimates. Only a few studies have incorporated the spatial layout of PV panels in the solar energy generation estimates, and none have simultaneously considered PV panel size, orientation, and rooftop structure. We address this limitation with a new spatially explicit optimization framework to enhance the accuracy of rooftop solar energy assessments. We consider both the roof's structural configuration and the shape and size of the panels in a novel maximum cover spatial optimization model. After applying the framework to three different types of rooftops (flat roof, pitched roof, and complex roof), we find that conventional methods can lead to a nearly 60% overestimation of energy potential compared to the optimized panel layout. Our work illustrates the importance of considering panel size and rooftop characteristics and offers a mechanism for designing more efficient rooftop PV systems. [ABSTRACT FROM AUTHOR]